Currently, there are no practical, scientifically reliable, and effective mechanisms to share real clinical data without compromising the data, or the identity of individuals, or other sensitive personal information to whom the data pertains. Cohort stratification approaches looking at large data archives may be misused by various actors aiming for re-identification of specific cases. To advance scientific understanding of the human conditions, the usefulness of releasing sifted de-identified data for research purposes trades off with the potential risk to re-identify individuals by narrowly stratifying sub cohorts in the entire data archive based on repeated mapping of known features for the specific case. Thus, an improved method is needed for creating data sets without compromising the identity of individuals or entities to whom the data pertains
This section provides background information related to the present disclosure which is not necessarily prior art.